Metacell integration

library loading

library(SuperCell)
library(Seurat)
#library(zellkonverter)
library(SingleCellExperiment)
library(ggplot2)
library(harmony)
library(reshape2)

In this tutorial we will make a short reanalysis of a large single cell transcriptome atlas of COVID19 at the metacell level. The orignal study gathered 1.4 millions of cells distributed in 284 samples coming from 196 patients. Here we will focus on a subset of 26 fresh PBMC samples.

Analysis of one sample from covid 19 dataset

We start by analyzing a fresh PBMC sample from an aged patient that deceased from a severe COVID 19. We will mainly consider the fist cell annotation to major PBMC cell types coming from the original study (‘majorType’ column in the metadata).

As in the original study we will discard immunoglobuline, ribosomal protein and mitochondrial genes for the dimension reduction analysis and the metacell construction.

These gene lists of genes were retrieved from the genenames website. In this tutorial we provide you the whole gene blacklist as an R object.

gene_blacklist <- readRDS("../data/gene_blacklist.rds")

Analysis at the single cell level with Seurat

Quality control (gene/cell filtering) was already done in the original study. We go directly to dimension reduction on highly variable genes

pbmc <- readRDS("../data/pbmc_COVID19_sce/S-S086-2_sce.rds")

sceRawToSeurat<- function(pbmc,nfeatures = 1500) {
pbmc <- CreateSeuratObject(counts = assay(pbmc),meta.data = data.frame(colData(pbmc)))
pbmc <- FindVariableFeatures(pbmc,nfeatures = nfeatures)
VariableFeatures(pbmc) <- VariableFeatures(pbmc)[!VariableFeatures(pbmc) %in% gene_blacklist]
pbmc <- NormalizeData(pbmc)
}

pbmc <- sceRawToSeurat(pbmc)

First we can do a Principal Component Analysis (PCA) of this sample with the Seurat package.

pbmc <- ScaleData(pbmc)
pbmc <- RunPCA(pbmc, npcs = 20)
ElbowPlot(pbmc) 

PCAPlot(pbmc,group.by = "majorType")

We can compute a 2D UMAP on the 20 first components of the PCA for visualization

pbmc <-RunUMAP(pbmc, dims = c(1:20))
UMAPPlot(pbmc, group.by = "majorType")

#UMAPPlot(pbmc, group.by = "celltype") + NoLegend()

We make a metacell Seurat object from the single cells of the sample. We assign metacell to metadata label (majorType, celltype) with the maximum absolute abundance within metacell thanks to the supercell_assign* function. We compute purity of metacells according to their assignment to the majorType annotation.

makeSeuratSC <- function(pbmc,
                         genes = NULL,
                         metaFields = c("majorType","sampleID","Age","Sex","celltype","PatientID","SARS.CoV.2","Outcome","datasets","CoVID.19.severity","Sample.time"),
                         returnSC = F) {
  
  if(is.null(genes)) {
    genes <- VariableFeatures(pbmc)
  }

SC <- SCimplify(GetAssayData(pbmc,slot = "data"),  # normalized gene expression matrix 
                 n.pc = 20,
                 k.knn = 5, # number of nearest neighbors to build kNN network
                 gamma = 20, # graining level
                 genes.use = genes )# will be the ones used for integration if input is seurat integrated data


SC$purity <- supercell_purity(clusters = pbmc$majorType,
                           supercell_membership = SC$membership)


#boxplot(SC$purity)
for (m in metaFields) {
SC[[m]]<- supercell_assign(clusters = pbmc@meta.data[,m], # single-cell assigment to cell lines (clusters)
                                    supercell_membership = SC$membership, # single-cell assignment to super-cells
                                    method = "absolute")
}

GE <- supercell_GE(as.matrix(GetAssayData(pbmc,slot = "data")),groups = SC$membership)

seuratSC <- supercell_2_Seurat(SC.GE = GE,SC,fields = c(metaFields,"purity"))

res <- seuratSC

if (returnSC) {
  res <- list(seuratSC = seuratSC,SC = SC)
}


return(res)
}

supercells <- makeSeuratSC(pbmc,returnSC = T)

## [1] "Done: NormalizeData"
## [1] "Doing: data to normalized data"
## [1] "Doing: weighted scaling"
## [1] "Done: weighted scaling"

We use the Seurat workflow to analyse the sample at the metacell level. Data scaling and PCA computation are weighted according to metacell size with the supercell_2_Seurat function we just used.

seuratSC <- supercells$seuratSC
seuratSC <- RunUMAP(seuratSC,dims = c(1:20))

We compute the UMAP dimension reduction on the weighted PCA results for visualization.

UMAPPlot(seuratSC,group.by = "majorType")

We can use the Seurat workflow without taking into account the sample weights by restarting from the data scaling step. This will overwrite the weighted downstream analysis results in the Seurat object.

seuratSC <- ScaleData(seuratSC)
seuratSC <- RunPCA(seuratSC, npcs = 20)
seuratSC <- RunUMAP(seuratSC,dims = c(1:10))
UMAPPlot(seuratSC,group.by = "majorType")

To be noted that the splits in the CD8 and DC majorType assigned metacells can be explained by the second level of clustering provided in the original study (celltype column in the metadata).

UMAPPlot(seuratSC,group.by = "celltype") + NoLegend()

We can check the distribution of metacell purities and sizes obtained.

ggplot(seuratSC@meta.data,aes(x=orig.ident,y=purity)) + geom_boxplot() + 
  ggplot(seuratSC@meta.data,aes(x=orig.ident,y=size)) + geom_boxplot() 

table(pbmc$majorType)

## 
##      B    CD4    CD8     DC   Mega   Mono     NK    Neu Plasma 
##    586   3162   3453     33    119   3273   2103      4    125

table(seuratSC$majorType)

## 
##      B    CD4    CD8     DC   Mega   Mono     NK Plasma 
##     42    151    177      4      9    161     87     12

Neu <- colnames(pbmc[,pbmc$majorType == "Neu"])
Neu

## [1] "ATTCTACTCATGTCCC-113" "CCATTCGCATACGCCG-113" "CCGGGATTCGTGGGAA-113"
## [4] "TTGTAGGTCTGCTGTC-113"

seuratSC$majorType[supercells$SC$membership[Neu]]

##    399    195    354    429 
## "Mono" "Mono" "Mono" "Mono"

We can see that for this PBMC sample the 4 single cell annotated as Neutrophils in the original study were merged with Monocytes at the metacell level. To completely match the original study results one possible strategy would be to make metacells per PBMC types or to use the cell.split.condition option of the SCimplify function. This will result in completely pure metacells according to the original annotation.

gene correlation analysis

The drop out noise is reduced with metacell analysis.

VlnPlot(pbmc, features = 'nFeature_RNA') 

VlnPlot(seuratSC, feature = 'nFeature_RNA')

This results in a better observation of gene-gene expression correlation. To illustrate this we can look for correlations of expression of CXCL8, one cytokine that came out of the original study that migh be involved in severe COVID19, and transcription factors that potentially regulate it.

gene<-as.matrix(GetAssayData(seuratSC)["CXCL8",])
correlations<-apply(as.matrix(GetAssayData(seuratSC)),1,function(x){cor(gene,x)})

tf <- read.table("../data/transcription.factor.activity.GO0003700.symbol.list")

correlations <- correlations[names(correlations) %in% tf$V1]
head(sort(abs(correlations),decreasing = T),n = 10)

##    ZNF467     KLF10      KLF4      SPI1     CREB5      GAS7   ZNF385A       FOS 
## 0.7719651 0.7452915 0.7162176 0.7162118 0.7122388 0.7077978 0.7016751 0.7013149 
##     CEBPD      BCL6 
## 0.6821084 0.6713770

FeatureScatter(object = pbmc, feature1 = "CXCL8", feature2 = 'KLF10',group.by = "majorType")

FeatureScatter(object = seuratSC, feature1 = "CXCL8", feature2 = 'KLF10',group.by = "majorType")

FeatureScatter(object = pbmc, feature1 = "CXCL8", feature2 = 'FOS',group.by = "majorType")

FeatureScatter(object = seuratSC, feature1 = "CXCL8", feature2 = 'FOS',group.by = "majorType")

We can also use the supercell_GeneGenePlot to have a view of the size of the metacells. It outputs a weighted correlation according to supercell sizes.

supercell_GeneGenePlot(GetAssayData(seuratSC),
                       gene_x = "CXCL8",gene_y = "FOS",
                       supercell_size = seuratSC$size,
                       clusters = seuratSC$majorType)

## $p

## 
## $w.cor
## $w.cor$CXCL8_FOS
## [1] 0.7602999
## 
## 
## $w.pval
## $w.pval$CXCL8_FOS
## [1] 0

supercell_GeneGenePlot(GetAssayData(seuratSC),
                       gene_x = "CXCL8",gene_y = "KLF10",
                       supercell_size = seuratSC$size,
                       clusters = seuratSC$majorType)

## $p

## 
## $w.cor
## $w.cor$CXCL8_KLF10
## [1] 0.8023985
## 
## 
## $w.pval
## $w.pval$CXCL8_KLF10
## [1] 0

We can also better appreciate the anticorrelation between CCND2 cycline gene and CDKN1A, coding for a cell cycle inhibitor proteine.

FeatureScatter(object = pbmc, feature1 = "CCND2", feature2 = 'CDKN1A',group.by = "majorType")

supercell_GeneGenePlot(GetAssayData(seuratSC),
                       gene_x = "CCND2",gene_y = "CDKN1A",
                       supercell_size = seuratSC$size,
                       clusters = seuratSC$majorType)

## $p

## 
## $w.cor
## $w.cor$CCND2_CDKN1A
## [1] -0.3245677
## 
## 
## $w.pval
## $w.pval$CCND2_CDKN1A
## [1] 3.805634e-313

Data integration at the metacell level

At least 16GB of memory are required to complete this analysis.

If you have more than 20GB, you should be able to integrate all the files we provided into ../data/pbmc_COVID19_sce. (26 data sets, about 200,000 unique cells).

If you have less than 20GB of memory, you should be able to integrate all the male samples (which are more evenly distributed across the different conditions than the female samples). We provide you with the list of male samples in the file ../data/lowMemFileList.rds (17 data sets, about 130,000 individual cells).

If you have less than 16GB of memory, you can try to integrate a small subset of 5~6 samples, but the downstream analysis we propose will not be very meaningful.

We will now integrate at the metacell level a subset of 26 samples of fresh PBMCs from the original study gathering around 200 000 cells.

We will use a gamma of 20 (10 000 metacells if you process the 26 data sets).

files <- list.files("../data/pbmc_COVID19_sce",full.names = T)

# Uncomment if you have less than 20GB of memory
# files <- readRDS("../data/lowMemFileList.rds")

# Uncomment if you less than 16GB of memory
#files <- files[c(1:6)]

SC.list <- list()
SC.list[["S-S086-2"]] <- seuratSC
for (f in files[-which(files == "../data/pbmc_COVID19_sce/S-S086-2_sce.rds")]) {
  smp <- readRDS(f)
  smp <- sceRawToSeurat(smp)
  seuratSC <- makeSeuratSC(smp)
  SC.list[[seuratSC$sampleID[1]]] <- seuratSC
}

## [1] "Done: NormalizeData"
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We select the highly variable genes accross samples for integration using the Seurat procedure.

features <- SelectIntegrationFeatures(SC.list,nfeatures = 1500)

features <- features[!features %in% gene_blacklist]

Seurat integration workflow

First we will use the Seurat integration workflow for large datasets using a reference based integration and the RPCA reduction dimension method.

for (i in 1:length(SC.list)) {
  SC.list[[i]] <- RenameCells(SC.list[[i]],add.cell.id = unique(SC.list[[i]]$sampleID))
  SC.list[[i]] <- ScaleData(SC.list[[i]],features = features)
  SC.list[[i]] <- RunPCA(SC.list[[i]] ,features = features,npcs = 20)
}

The subset of samples come from male and female patients. As gender is often a large source of variation at the transcriptomic level, we will use the largest male and female samples as reference.

reference <- which(c("S-S086-2","S-M064") %in% names(SC.list)) 



  
anchors <- FindIntegrationAnchors(object.list = SC.list,
                                  reference = reference, 
                                  reduction = "rpca",
                                  anchor.features = features,
                                  dims = 1:20)

integrated <- IntegrateData(anchorset = anchors, dims = 1:20)

We can now use the classical Seurat workflow on the integrated object

DefaultAssay(integrated) = "integrated"
integrated <- ScaleData(integrated, verbose = T)
integrated <- RunPCA(integrated, verbose = FALSE)
integrated <- RunUMAP(integrated, dims = 1:20)

We check that our integration correctly mixed the different samples in the reduced space by preserving differences between the different PBMC types. We can also check that we don’t have a gender effect in the integrated data.

UMAPPlot(integrated,group.by = "sampleID")

UMAPPlot(integrated,group.by = "majorType")

UMAPPlot(integrated,group.by = "Sex")

Now we will use Harmony, an other integration method. We will use it inside the Seurat framework.

DefaultAssay(integrated) <- "RNA"
integrated <- ScaleData(integrated,features = features)
integrated <- RunPCA(integrated, npcs = 20, verbose = FALSE,features = features)

integrated <- RunHarmony(integrated,c("sampleID","datasets"),theta = c(2.5,1.5))
integrated <- RunUMAP(integrated,reduction = "harmony",
                      reduction.name = "umap.harmony",
                      dims = 1:20)

DimPlot(integrated,group.by = "sampleID", reduction = "umap.harmony")

DimPlot(integrated,group.by = "majorType", reduction = "umap.harmony")

The original study mainly focused on the analysis of variations in the cell type composition according to COVID19 severity (control, mild/moderate, severe) and the time of sampling (control, progression, convalescence).

DimPlot(integrated,group.by = "Sample.time", reduction = "umap.harmony") 

DimPlot(integrated,group.by = "CoVID.19.severity", reduction = "umap.harmony")

In this tutorial we will make a short analysis of this at the metacell level regarding the first level of annotation (PMBC major type). We can compute the observed versus expected cell number ratio for each PBMC type for the different conditions. We have to take into account the supercell size for this analysis.

majorTypeCounts <- aggregate(integrated$size, by=list(majorType = integrated$majorType,Severity = integrated$CoVID.19.severity,Time = integrated$Sample.time), FUN=sum)


majorTypeCounts$group = paste(majorTypeCounts$Severity,majorTypeCounts$Time,sep = "_")

contingencyTable <- xtabs(x ~ group + majorType,data = majorTypeCounts)

res <- chisq.test(contingencyTable)

Roe <- res$observed/res$expected

As in the original study we observe an increase in the Megakaryocytes cell proportion during the progression of severe/critical COVID compare to the other condition.

melted_Roe <- melt(Roe, na.rm = TRUE)
# Heatmap
ggplot(data = melted_Roe, aes(majorType,group, , fill = value))+
 geom_tile() + scale_fill_gradient2(low = "blue", high = "red", mid = "white", 
   midpoint = 1, space = "Lab",
   name="Ro/e") +
  theme_minimal()+ 
 theme(axis.text.x = element_text(angle = 45, vjust = 1, 
    size = 12, hjust = 1))+
 coord_fixed()

Without the few metacell assigned to macrophages found in the control samples that overwrite the results:

ggplot(data = melted_Roe[melted_Roe$majorType != "Macro",], aes(majorType,group, , fill = value))+
 geom_tile() + scale_fill_gradient2(low = "blue", high = "red", mid = "white", 
   midpoint = 1, space = "Lab",
   name="Ro/e") +
  theme_minimal()+ 
 theme(axis.text.x = element_text(angle = 45, vjust = 1, 
    size = 12, hjust = 1))+
 coord_fixed()

We can do a differentially expressed gene analysis to characterized the gene markers of this population that seem to support progression of severe/critical COVID. We perform this analysis at the metacell level (on averaged normalized counts per metacell).

Idents(integrated) <- "majorType"
markersMega <- FindMarkers(integrated,ident.1 = "Mega",only.pos = T)
markersMega <- markersMega[markersMega$p_val_adj< 0.05,]
markersMega[order(markersMega$avg_log2FC,decreasing = T),]

##                     p_val avg_log2FC pct.1 pct.2     p_val_adj
## PPBP         7.343396e-78  6.9739255 1.000 0.542  2.051965e-73
## TUBB1       1.369173e-118  5.6194829 1.000 0.250 3.825880e-114
## PF4          1.071578e-90  5.6174591 1.000 0.387  2.994310e-86
## HIST1H2AC    2.864705e-72  5.3653535 1.000 0.731  8.004846e-68
## CAVIN2       2.357085e-99  5.2753922 1.000 0.329  6.586401e-95
## ACRBP       1.829055e-102  5.2367713 1.000 0.313  5.110928e-98
## RGS18        1.818439e-79  4.9225969 1.000 0.506  5.081265e-75
## GP9         5.546363e-174  4.8720905 1.000 0.147 1.549820e-169
## TSC22D1      6.999086e-96  4.7060554 1.000 0.348  1.955755e-91
## MPIG6B      4.634917e-117  4.6369998 0.991 0.246 1.295135e-112
## SPARC        5.065096e-98  4.5387751 1.000 0.335  1.415340e-93
## GNG11       1.338831e-111  4.5275871 1.000 0.273 3.741097e-107
## TMEM40      1.451894e-179  4.1880384 0.991 0.138 4.057029e-175
## TUBA4A       1.173480e-68  4.0509572 1.000 0.906  3.279054e-64
## CLU          9.698693e-77  3.9565073 0.981 0.465  2.710106e-72
## PTCRA       9.085600e-300  3.9356358 0.991 0.071 2.538789e-295
## CMTM5       2.390091e-229  3.9287965 1.000 0.103 6.678631e-225
## MMD          2.652647e-83  3.9124558 1.000 0.453  7.412291e-79
## NRGN         1.110951e-77  3.8322352 1.000 0.542  3.104330e-73
## TPM4         3.322777e-65  3.8132802 1.000 0.912  9.284837e-61
## MPP1         6.369813e-73  3.7923157 1.000 0.602  1.779917e-68
## GRAP2        3.497336e-73  3.7904823 1.000 0.621  9.772606e-69
## RGS10        5.455530e-68  3.7545251 1.000 0.916  1.524439e-63
## RAP1B        3.782094e-67  3.7161719 1.000 0.985  1.056831e-62
## LIMS1        3.802598e-66  3.7126724 0.991 0.843  1.062560e-61
## MYL9        1.719241e-106  3.7064382 0.972 0.257 4.804075e-102
## HIST1H3H    7.506411e-103  3.6625307 0.991 0.291  2.097517e-98
## YWHAH        7.347504e-64  3.6166561 0.991 0.781  2.053113e-59
## NT5C3A       3.086653e-67  3.5764202 1.000 0.865  8.625034e-63
## ESAM        5.776516e-181  3.5690281 0.972 0.129 1.614132e-176
## MAX          1.310628e-66  3.5599763 1.000 0.952  3.662287e-62
## PTGS1        9.981906e-95  3.5522458 1.000 0.356  2.789244e-90
## TRIM58      1.351251e-127  3.5439518 0.972 0.203 3.775800e-123
## CTSA         2.709868e-67  3.4666203 1.000 0.885  7.572185e-63
## RUFY1        3.777995e-73  3.4400121 1.000 0.628  1.055685e-68
## F13A1        2.399869e-84  3.4110772 0.981 0.378  6.705955e-80
## CLEC1B      2.431521e-121  3.3829744 0.981 0.222 6.794399e-117
## HIST1H2BJ   7.458737e-126  3.3276762 1.000 0.226 2.084195e-121
## TAGLN2       2.059878e-68  3.2857938 1.000 0.998  5.755918e-64
## C2orf88     1.119232e-131  3.2634341 0.963 0.190 3.127471e-127
## TREML1      2.764922e-157  3.2232758 0.981 0.158 7.726023e-153
## PGRMC1       4.832107e-72  3.1830420 1.000 0.685  1.350236e-67
## ITGA2B      4.956780e-161  3.1756464 0.991 0.158 1.385073e-156
## RAB11A       9.959685e-66  3.1706711 1.000 0.940  2.783035e-61
## MAP3K7CL     4.190299e-73  3.1560255 0.981 0.514  1.170895e-68
## NCOA4        1.248128e-62  3.1379038 1.000 0.926  3.487644e-58
## GSTO1        2.835036e-56  3.1079719 0.991 0.920  7.921940e-52
## TLN1         1.215672e-59  3.0575100 1.000 0.961  3.396951e-55
## FERMT3       9.961996e-56  3.0247397 0.991 0.952  2.783680e-51
## VCL          7.676626e-67  3.0100747 0.991 0.782  2.145080e-62
## PDLIM1       1.498277e-77  3.0001736 0.991 0.445  4.186636e-73
## PTPN18       1.603420e-62  2.9325477 0.991 0.852  4.480436e-58
## BEX3         1.146923e-84  2.8819700 1.000 0.433  3.204847e-80
## NAP1L1       1.496767e-66  2.8804706 1.000 0.983  4.182416e-62
## AP003068.2  3.843168e-109  2.8696867 0.972 0.251 1.073896e-104
## TMEM140      2.250776e-65  2.8615610 0.953 0.548  6.289344e-61
## ILK          3.144326e-62  2.8564302 1.000 0.876  8.786191e-58
## KIF2A        7.775329e-67  2.7708350 1.000 0.874  2.172660e-62
## STOM         4.007211e-61  2.7260386 0.991 0.763  1.119735e-56
## ODC1         6.612067e-60  2.7174499 0.972 0.714  1.847610e-55
## NFE2         6.114892e-67  2.7152387 0.935 0.346  1.708684e-62
## RSU1         4.057717e-64  2.7077428 1.000 0.903  1.133848e-59
## CALM3        1.148436e-63  2.7035959 1.000 0.979  3.209075e-59
## FAM110A      1.205604e-43  2.6835797 0.916 0.687  3.368820e-39
## GPX4         8.706234e-63  2.6784640 1.000 0.988  2.432783e-58
## EIF2AK1      6.370642e-60  2.6605001 0.981 0.857  1.780148e-55
## RAB27B      2.915467e-100  2.6523426 0.963 0.268  8.146690e-96
## ETFA         1.073701e-65  2.6290838 1.000 0.881  3.000243e-61
## PF4V1       5.402475e-127  2.6257679 0.953 0.190 1.509614e-122
## MARCH2       4.760433e-76  2.6157620 1.000 0.546  1.330208e-71
## DAB2         9.110602e-86  2.6140086 0.953 0.322  2.545775e-81
## DMTN        4.356634e-139  2.6091859 0.925 0.156 1.217374e-134
## OAZ1         1.138064e-57  2.5977175 1.000 0.999  3.180093e-53
## NEXN         3.341564e-76  2.5767199 0.925 0.348  9.337332e-72
## SMOX        6.432445e-206  2.5564662 0.972 0.110 1.797418e-201
## SLC40A1      6.549881e-75  2.5247252 0.972 0.427  1.830233e-70
## CA2         1.503361e-106  2.5120752 0.953 0.240 4.200842e-102
## MYLK        1.297477e-108  2.5095504 0.963 0.246 3.625541e-104
## CDKN1A       3.017902e-64  2.4844153 0.981 0.486  8.432924e-60
## GUCY1B1     2.011203e-127  2.4763974 0.972 0.203 5.619904e-123
## OST4         9.905373e-69  2.4550259 1.000 0.998  2.767858e-64
## R3HDM4       4.514358e-61  2.4527496 1.000 0.883  1.261447e-56
## ADIPOR1      4.755157e-53  2.4494513 0.963 0.860  1.328733e-48
## SMIM3        4.528998e-79  2.4282733 0.991 0.461  1.265538e-74
## RNF11        4.033438e-59  2.4259965 0.981 0.761  1.127064e-54
## PLA2G12A     1.888402e-72  2.4057637 0.981 0.541  5.276763e-68
## LMNA         5.342916e-73  2.3921686 0.963 0.415  1.492971e-68
## H2AFJ        1.938963e-55  2.3864362 0.981 0.882  5.418046e-51
## ACTN1        7.939342e-65  2.3702170 0.972 0.621  2.218490e-60
## PRKAR2B     1.026559e-113  2.3338496 0.981 0.246 2.868513e-109
## H3F3A        2.366433e-56  2.3156230 1.000 1.000  6.612523e-52
## CNST         5.520655e-46  2.3126812 0.944 0.809  1.542636e-41
## GAS2L1      3.573659e-108  2.3062019 0.916 0.206 9.985875e-104
## SNCA        1.292524e-106  2.2976775 0.972 0.258 3.611699e-102
## GMPR        4.004290e-119  2.2922754 0.963 0.213 1.118919e-114
## RASGRP2      1.419702e-54  2.2792865 0.991 0.964  3.967074e-50
## TPST2        1.916056e-50  2.2720952 0.963 0.854  5.354035e-46
## AC147651.1  6.221279e-219  2.2422547 0.963 0.099 1.738412e-214
## WBP2         3.587594e-61  2.2303000 1.000 0.920  1.002481e-56
## TMBIM1       1.284256e-54  2.2275085 0.981 0.887  3.588597e-50
## YWHAZ        6.499557e-59  2.2200041 1.000 0.999  1.816171e-54
## CCND3        1.060959e-47  2.2166474 1.000 0.983  2.964639e-43
## ZYX          9.782530e-32  2.2115371 1.000 0.935  2.733532e-27
## PRDX6        4.865923e-59  2.2107954 1.000 0.966  1.359685e-54
## CARD19       6.965770e-63  2.2031097 0.981 0.700  1.946445e-58
## WDR1         2.214920e-58  2.1763029 1.000 0.968  6.189151e-54
## DNAJB6       3.876991e-49  2.1732361 0.991 0.937  1.083347e-44
## CD9          5.442145e-76  2.1670729 0.925 0.328  1.520699e-71
## SNAP23       1.034429e-61  2.1644924 0.991 0.897  2.890504e-57
## GP1BA        0.000000e+00  2.1586664 0.907 0.052  0.000000e+00
## ARHGAP18     1.641839e-67  2.1486918 0.972 0.566  4.587790e-63
## CMIP         3.806205e-58  2.1260658 0.972 0.716  1.063568e-53
## RAB32        3.187432e-67  2.1173491 0.925 0.357  8.906640e-63
## PARVB        9.435945e-44  2.1059391 0.888 0.605  2.636686e-39
## LAMTOR1      5.725636e-56  2.0795333 1.000 0.976  1.599914e-51
## MFSD1        2.442529e-60  2.0701596 0.991 0.816  6.825158e-56
## RIOK3        1.143793e-45  2.0691391 0.944 0.921  3.196102e-41
## TUBA1C       1.758646e-47  2.0489714 0.972 0.858  4.914185e-43
## ITM2B        2.550433e-51  2.0440351 1.000 0.997  7.126675e-47
## LINC00989   3.007613e-222  2.0422163 0.963 0.096 8.404174e-218
## TPM1         3.606997e-68  2.0352095 0.944 0.470  1.007903e-63
## DAPP1        3.905654e-57  2.0334741 0.981 0.658  1.091357e-52
## RIPOR2       6.578503e-42  2.0291592 1.000 0.991  1.838231e-37
## MYL12A       9.328502e-54  2.0288038 1.000 0.999  2.606663e-49
## TUBA8        0.000000e+00  2.0273743 0.963 0.048  0.000000e+00
## TIMP1        3.948581e-50  2.0184633 1.000 0.870  1.103352e-45
## FRMD3        4.026812e-67  2.0135126 0.935 0.425  1.125212e-62
## XPNPEP1      1.236807e-55  2.0049435 0.963 0.693  3.456009e-51
## ARHGAP6     3.695517e-221  1.9871985 0.991 0.105 1.032638e-216
## CTTN        2.152597e-139  1.9861507 0.935 0.160 6.015002e-135
## LAT          5.593737e-50  1.9785757 0.991 0.727  1.563058e-45
## AKIRIN2      2.182696e-43  1.9627046 0.972 0.919  6.099106e-39
## CAPZA2       1.207281e-55  1.9266343 1.000 0.944  3.373506e-51
## NDUFA6       5.062248e-49  1.9263512 1.000 0.953  1.414544e-44
## CD99         8.374875e-43  1.9250567 1.000 0.982  2.340191e-38
## ICAM2        2.557495e-43  1.9201025 0.981 0.900  7.146408e-39
## TNS1        1.400846e-117  1.9081667 0.907 0.178 3.914383e-113
## ITGB3       3.286520e-257  1.9035641 0.888 0.066 9.183524e-253
## CLDN5        0.000000e+00  1.8960807 0.841 0.037  0.000000e+00
## GFI1B       2.117830e-174  1.8778844 0.935 0.121 5.917853e-170
## HIST2H2AA4   1.204453e-44  1.8674150 0.916 0.615  3.365603e-40
## THBS1        4.768385e-49  1.8500415 0.925 0.633  1.332430e-44
## BIN2         8.662594e-38  1.8458416 1.000 0.978  2.420589e-33
## AC114752.2  2.174391e-261  1.8442714 0.897 0.066 6.075901e-257
## GLUL         3.291718e-33  1.8290017 0.944 0.815  9.198047e-29
## NORAD        4.447716e-58  1.8270190 0.991 0.880  1.242825e-53
## LDLRAP1      3.529597e-49  1.8200090 0.953 0.647  9.862753e-45
## ARF1         5.933444e-49  1.8143296 1.000 0.993  1.657982e-44
## AP001189.1  1.443939e-173  1.8063541 0.963 0.131 4.034798e-169
## MGLL        9.098840e-110  1.7946134 0.944 0.220 2.542489e-105
## EGFL7       1.082499e-185  1.7895811 0.841 0.085 3.024827e-181
## SNN          9.761356e-57  1.7796474 0.925 0.501  2.727616e-52
## DERA         2.505083e-47  1.7721738 0.907 0.646  6.999955e-43
## AC090409.1   0.000000e+00  1.7671706 0.953 0.039  0.000000e+00
## FAXDC2      2.941422e-178  1.7654674 0.925 0.115 8.219217e-174
## TGFB1        2.438165e-54  1.7513295 1.000 0.949  6.812964e-50
## STON2       1.004057e-199  1.7502433 0.935 0.102 2.805636e-195
## CDKN2D       1.109487e-38  1.7501688 0.944 0.852  3.100240e-34
## ANO6         1.286249e-57  1.7419751 0.972 0.751  3.594165e-53
## MED12L      1.036314e-200  1.7320790 0.897 0.091 2.895771e-196
## SEC14L1      1.783657e-38  1.7196218 0.972 0.849  4.984073e-34
## PKM          1.576644e-32  1.7047148 0.981 0.990  4.405615e-28
## ALOX12      4.831236e-233  1.7001863 0.944 0.087 1.349992e-228
## SH3BGRL2    3.713423e-169  1.6992608 0.925 0.123 1.037642e-164
## PDCD10       2.319903e-49  1.6910744 0.972 0.908  6.482505e-45
## C19orf33    2.594053e-207  1.6770046 0.822 0.071 7.248562e-203
## HIST1H1C     3.790627e-44  1.6715367 0.944 0.788  1.059215e-39
## TLK1         1.781220e-63  1.6594407 1.000 0.839  4.977262e-59
## PTGIR        4.827762e-47  1.6583668 0.850 0.431  1.349022e-42
## TALDO1       1.271365e-38  1.6512866 1.000 0.964  3.552574e-34
## CCNG1        9.795723e-35  1.6481784 0.925 0.869  2.737219e-30
## MIR4435-2HG  1.507140e-55  1.6453737 0.972 0.655  4.211402e-51
## VDAC3        3.952310e-57  1.6449944 1.000 0.903  1.104394e-52
## IFRD1        1.099848e-38  1.6436645 0.916 0.801  3.073306e-34
## CORO1C       6.649611e-56  1.6421629 0.944 0.536  1.858101e-51
## FTH1         8.265325e-43  1.6324280 1.000 1.000  2.309580e-38
## RDH11        3.235857e-53  1.6291787 0.953 0.792  9.041956e-49
## DYNLL1       5.615484e-44  1.6215982 1.000 0.959  1.569135e-39
## BCL2L1       1.067458e-51  1.6186812 0.916 0.601  2.982797e-47
## RBX1         2.037297e-47  1.6178705 1.000 0.973  5.692820e-43
## INKA1       9.306606e-134  1.6002047 0.813 0.114 2.600545e-129
## LYL1         2.721129e-46  1.5910366 0.850 0.432  7.603650e-42
## TNFSF4      2.686233e-268  1.5841580 0.832 0.053 7.506140e-264
## GP6         2.854612e-237  1.5806140 0.907 0.077 7.976644e-233
## VIM-AS1      3.418000e-84  1.5732294 0.981 0.378  9.550919e-80
## NAT8         0.000000e+00  1.5732050 0.804 0.030  0.000000e+00
## CAP1         3.168936e-39  1.5708896 1.000 0.981  8.854958e-35
## MINDY1       4.763359e-75  1.5663388 0.916 0.343  1.331025e-70
## LTBP1        0.000000e+00  1.5656600 0.897 0.034  0.000000e+00
## HIST1H2BC    1.546339e-63  1.5642955 0.935 0.470  4.320934e-59
## MTPN         4.456621e-37  1.5557001 0.963 0.966  1.245313e-32
## ABCC3       3.240209e-112  1.5520566 0.963 0.228 9.054115e-108
## EMC3         7.363636e-58  1.5478175 0.991 0.916  2.057621e-53
## ZNF185       5.054147e-84  1.5463074 0.925 0.294  1.412280e-79
## SMIM5       1.723366e-234  1.5461303 0.888 0.073 4.815602e-230
## SLA2         1.429612e-57  1.5440242 0.944 0.514  3.994765e-53
## CD226        1.142727e-58  1.5329830 0.935 0.544  3.193122e-54
## ELF1         1.021507e-26  1.5321534 0.953 0.973  2.854397e-22
## SQSTM1       1.963371e-34  1.5268909 0.991 0.970  5.486248e-30
## ENKUR       3.081702e-262  1.5137902 0.860 0.059 8.611199e-258
## LGALS12     2.022312e-175  1.5018363 0.897 0.107 5.650947e-171
## FRMD4B       1.011526e-46  1.4983496 0.860 0.434  2.826507e-42
## AL731557.1   0.000000e+00  1.4876766 0.981 0.057  0.000000e+00
## NUTF2        2.413745e-46  1.4859142 0.972 0.905  6.744727e-42
## IFI27        1.703478e-15  1.4831030 0.664 0.401  4.760027e-11
## HLA-E        2.572529e-46  1.4755627 1.000 1.000  7.188418e-42
## CAPN1        1.387566e-46  1.4744873 0.944 0.883  3.877275e-42
## SOD2         1.928668e-44  1.4737044 0.981 0.930  5.389276e-40
## SLC44A2      3.801980e-48  1.4583548 0.963 0.890  1.062387e-43
## LEPROT       2.711495e-54  1.4556585 0.972 0.783  7.576732e-50
## CYTOR        3.572011e-42  1.4448973 0.953 0.799  9.981270e-38
## PNMA1        1.563690e-63  1.4446440 0.897 0.400  4.369419e-59
## HIST1H4H     7.180020e-23  1.4418265 0.617 0.343  2.006313e-18
## GATA1        0.000000e+00  1.4388256 0.794 0.012  0.000000e+00
## GADD45A      8.872310e-60  1.4288636 0.897 0.413  2.479190e-55
## LYPLAL1      2.050746e-43  1.4285988 0.897 0.651  5.730398e-39
## PSTPIP2      1.466180e-51  1.4274807 0.944 0.609  4.096946e-47
## SIAH2        1.482725e-16  1.4241101 0.701 0.569  4.143178e-12
## PIP4P2       7.257828e-60  1.4234403 0.963 0.591  2.028055e-55
## LCN2        4.039321e-297  1.4222448 0.869 0.052 1.128708e-292
## AC123912.4  2.527945e-232  1.4098637 0.776 0.054 7.063838e-228
## AP000547.3   1.366486e-92  1.4079876 0.925 0.261  3.818373e-88
## HIST1H2BH    1.190993e-99  1.4022654 0.822 0.162  3.327991e-95
## INSIG1       7.843459e-42  1.3994269 0.925 0.712  2.191698e-37
## MOB1B        8.643112e-55  1.3942843 0.897 0.486  2.415145e-50
## HACD4        5.912853e-45  1.3912950 0.972 0.910  1.652228e-40
## GSN          5.500991e-46  1.3877797 0.935 0.568  1.537142e-41
## MAPRE2       2.195241e-45  1.3785170 0.972 0.872  6.134162e-41
## YPEL5        2.791833e-51  1.3781474 1.000 0.941  7.801218e-47
## TMEM50A      1.694031e-43  1.3731437 0.981 0.982  4.733631e-39
## LGALSL       0.000000e+00  1.3681928 0.869 0.050  0.000000e+00
## HIST1H2AG    1.443853e-58  1.3656214 0.841 0.324  4.034559e-54
## TMEM91       1.765846e-57  1.3550905 0.944 0.492  4.934304e-53
## SH3BGRL3     1.755442e-22  1.3471029 1.000 1.000  4.905232e-18
## RAP2B        1.684371e-36  1.3434418 0.944 0.822  4.706637e-32
## FHL1         2.311710e-73  1.3341024 0.860 0.272  6.459610e-69
## CMTM6        5.600453e-39  1.3318405 0.981 0.946  1.564935e-34
## SPNS1        1.703098e-51  1.3310926 0.944 0.733  4.758965e-47
## NDUFS5       1.411172e-30  1.3230913 0.991 0.986  3.943238e-26
## MKRN1        1.475250e-40  1.3189781 0.963 0.920  4.122291e-36
## SELP         0.000000e+00  1.3125252 0.925 0.051  0.000000e+00
## MOB1A        1.177983e-36  1.3124526 1.000 0.961  3.291637e-32
## C9orf16      5.276114e-41  1.3069542 0.991 0.961  1.474305e-36
## CYB5R3       3.232918e-45  1.3058304 0.972 0.834  9.033744e-41
## PDE5A       2.045737e-127  1.3033997 0.935 0.180 5.716402e-123
## MMRN1        0.000000e+00  1.3029894 0.822 0.039  0.000000e+00
## MCUR1        2.222865e-49  1.3015478 0.916 0.667  6.211353e-45
## EHD3        7.813802e-112  1.3008182 0.897 0.186 2.183411e-107
## MYH9         2.117303e-26  1.2975873 0.972 0.991  5.916381e-22
## ACTB         3.748459e-20  1.2945203 1.000 1.000  1.047432e-15
## SCN1B       3.583513e-110  1.2904813 0.935 0.215 1.001341e-105
## ENDOD1       4.677594e-71  1.2902699 0.925 0.387  1.307060e-66
## MYL6         1.215946e-18  1.2864160 1.000 1.000  3.397718e-14
## FKBP1A       5.744507e-33  1.2837066 1.000 0.975  1.605188e-28
## CCL5         5.422780e-28  1.2823672 1.000 0.785  1.515287e-23
## CD151        2.348147e-39  1.2718742 0.925 0.732  6.561427e-35
## RAB1B        2.054168e-36  1.2710733 0.944 0.937  5.739962e-32
## ARPC5        2.950163e-37  1.2694750 1.000 0.989  8.243641e-33
## TBXA2R      3.045929e-109  1.2676533 0.822 0.150 8.511240e-105
## RNF24        9.008066e-47  1.2637197 0.925 0.590  2.517124e-42
## TAL1        1.167523e-195  1.2597928 0.879 0.090 3.262408e-191
## MBNL1        3.084731e-22  1.2552899 1.000 0.996  8.619664e-18
## TUBB4B       1.354919e-37  1.2533300 0.972 0.876  3.786049e-33
## SSX2IP       1.778223e-74  1.2478650 0.850 0.265  4.968889e-70
## SVIP         5.358926e-56  1.2395616 0.963 0.680  1.497445e-51
## RAB4A        2.771518e-52  1.2374265 0.972 0.793  7.744453e-48
## TBPL1        6.763364e-31  1.2252158 0.888 0.793  1.889887e-26
## PLEK         1.969687e-17  1.2249602 0.981 0.848  5.503895e-13
## VAPA         4.464618e-29  1.2101092 0.981 0.974  1.247548e-24
## RAB37        1.622035e-48  1.2071530 0.963 0.754  4.532452e-44
## MLH3         7.519624e-73  1.2056115 0.963 0.462  2.101209e-68
## MFAP3L       0.000000e+00  1.2048223 0.888 0.047  0.000000e+00
## SPINT2       1.227283e-45  1.2044963 0.944 0.642  3.429396e-41
## MEIS1        2.001635e-75  1.1898404 0.738 0.171  5.593168e-71
## ELOVL7       0.000000e+00  1.1889815 0.897 0.053  0.000000e+00
## PYGL         1.247177e-51  1.1711203 0.907 0.389  3.484988e-47
## UBL4A        3.261687e-55  1.1667532 0.953 0.610  9.114133e-51
## WDR66        6.824025e-38  1.1665505 0.794 0.449  1.906837e-33
## BNIP2        4.703447e-32  1.1649460 0.981 0.924  1.314284e-27
## TPM3         4.783579e-28  1.1625683 1.000 0.999  1.336675e-23
## PRKAR1B      4.034469e-74  1.1585699 0.944 0.398  1.127352e-69
## ARPC1B       1.983816e-18  1.1576877 0.991 0.992  5.543377e-14
## F2R          5.638232e-52  1.1532982 0.897 0.420  1.575491e-47
## P2RX1        1.062986e-62  1.1501725 0.925 0.368  2.970302e-58
## SNX3         1.709566e-34  1.1413515 0.991 0.949  4.777040e-30
## MTURN       5.243275e-108  1.1402873 0.935 0.223 1.465128e-103
## DNM3        6.201641e-228  1.1383222 0.888 0.076 1.732925e-223
## AC010186.1  1.130407e-225  1.1288172 0.832 0.066 3.158696e-221
## HIST2H2BE    2.591464e-50  1.1270913 0.860 0.430  7.241328e-46
## SAT1         1.017476e-25  1.1235738 1.000 0.991  2.843133e-21
## KCTD20       3.958358e-44  1.1187479 0.925 0.744  1.106084e-39
## PPM1A        5.441020e-47  1.1184609 0.944 0.731  1.520384e-42
## SRGN         2.141148e-20  1.1115565 0.991 0.975  5.983009e-16
## CLIC1        2.133554e-14  1.1089035 1.000 0.991  5.961791e-10
## KIFC3        1.422963e-90  1.1058378 0.841 0.195  3.976185e-86
## CRBN         1.879219e-14  1.1023571 0.897 0.911  5.251103e-10
## SLC2A3       6.044119e-23  1.0984183 0.953 0.906  1.688908e-18
## TACC3        3.001535e-38  1.0942012 0.916 0.715  8.387190e-34
## IGF2BP3     1.125150e-128  1.0919475 0.785 0.111 3.144007e-124
## CCDC85B      5.456953e-17  1.0902718 0.925 0.888  1.524836e-12
## DEPP1        3.078471e-80  1.0865794 0.262 0.016  8.602172e-76
## APP          5.860649e-51  1.0863149 0.953 0.624  1.637641e-46
## AP001636.3  3.312130e-183  1.0861148 0.897 0.097 9.255085e-179
## HMGB1        2.727931e-37  1.0842534 1.000 0.999  7.622658e-33
## ARF4         1.508660e-24  1.0832345 0.963 0.918  4.215650e-20
## ASAH1        5.722534e-31  1.0822665 1.000 0.925  1.599048e-26
## CYB5R1       4.149553e-39  1.0750572 0.897 0.691  1.159509e-34
## SENCR        9.972209e-78  1.0689143 0.822 0.226  2.786534e-73
## TXNL4B       1.050417e-28  1.0673825 0.720 0.456  2.935181e-24
## ITGB1        1.309744e-39  1.0664465 0.991 0.902  3.659818e-35
## RBBP6        2.381757e-13  1.0657847 0.907 0.920  6.655343e-09
## NPTN         3.504263e-29  1.0628568 0.850 0.666  9.791961e-25
## AC008763.1  6.081967e-128  1.0611146 0.813 0.121 1.699484e-123
## MAP4K5       7.763810e-36  1.0596975 0.879 0.683  2.169441e-31
## RTN3         6.764202e-38  1.0565244 0.972 0.860  1.890121e-33
## SMIM1        5.331010e-70  1.0552878 0.710 0.167  1.489644e-65
## PTTG1IP      6.107811e-30  1.0552042 0.935 0.813  1.706706e-25
## NDUFAF3      1.530760e-35  1.0543198 0.953 0.923  4.277402e-31
## C12orf75     4.967499e-29  1.0534896 0.953 0.621  1.388068e-24
## CLIC4        2.179069e-50  1.0533850 0.832 0.365  6.088973e-46
## TNNC2       1.052797e-208  1.0523739 0.869 0.080 2.941830e-204
## RAB8A        2.725876e-39  1.0511654 0.972 0.914  7.616916e-35
## ERV3-1       3.127748e-38  1.0505816 0.785 0.454  8.739866e-34
## STRAP        2.251284e-20  1.0499757 0.953 0.936  6.290762e-16
## RAB10        2.394011e-32  1.0496201 0.972 0.906  6.689586e-28
## FAH          3.102378e-52  1.0489809 0.813 0.347  8.668975e-48
## GTPBP2       1.421736e-41  1.0481495 0.785 0.407  3.972756e-37
## PAIP2        2.065052e-35  1.0448556 1.000 0.975  5.770373e-31
## MYCT1        0.000000e+00  1.0415958 0.757 0.031  0.000000e+00
## FLNA         3.313024e-07  1.0378830 0.944 0.978  9.257582e-03
## ISCA1        1.281947e-46  1.0358226 0.963 0.832  3.582144e-42
## PRUNE1       4.613683e-53  1.0352409 0.869 0.446  1.289201e-48
## CMPK1        1.125022e-42  1.0264225 0.963 0.889  3.143649e-38
## WIPF1        1.204517e-29  1.0259363 0.991 0.975  3.365781e-25
## ABLIM3       0.000000e+00  1.0256229 0.860 0.046  0.000000e+00
## DSE          3.937210e-35  1.0244637 0.832 0.526  1.100175e-30
## UBAC2        2.722726e-41  1.0230068 0.944 0.910  7.608113e-37
## ABCC4        1.114047e-59  1.0218099 0.813 0.295  3.112983e-55
## KIAA0513     3.018775e-43  1.0200822 0.897 0.494  8.435362e-39
## C12orf76     2.494354e-36  1.0147766 0.879 0.740  6.969972e-32
## ARRB1        2.898000e-27  1.0145990 0.785 0.534  8.097882e-23
## UQCRH        4.717017e-33  1.0093311 1.000 0.996  1.318076e-28
## AMD1         9.102300e-41  1.0054950 0.953 0.899  2.543456e-36
## C1orf198    2.664247e-147  0.9973188 0.785 0.094 7.444704e-143
## CLCN3        4.771460e-46  0.9963321 0.907 0.655  1.333289e-41
## MFSD2B      1.289889e-278  0.9944178 0.785 0.044 3.604336e-274
## BEND2       3.894562e-213  0.9930740 0.897 0.085 1.088257e-208
## SEPT11       5.272213e-35  0.9921772 0.832 0.560  1.473214e-30
## TM2D2        7.803014e-33  0.9916185 0.804 0.570  2.180396e-28
## INKA2        2.010704e-88  0.9886209 0.701 0.126  5.618510e-84
## TMSB4X       6.127401e-17  0.9885763 1.000 1.000  1.712180e-12
## CENPT        1.235591e-33  0.9860357 0.860 0.680  3.452611e-29
## PPDPF        3.381131e-16  0.9799610 0.991 0.976  9.447894e-12
## MAP1A       3.862205e-233  0.9792438 0.832 0.062 1.079216e-228
## GNAS         2.786887e-28  0.9785978 0.991 0.970  7.787397e-24
## AGPAT1       3.161851e-44  0.9769910 0.897 0.681  8.835159e-40
## CAMTA1       3.027794e-41  0.9744854 0.953 0.846  8.460563e-37
## HIST1H2BK    1.103098e-59  0.9729913 0.953 0.544  3.082387e-55
## PPP1R14A     2.784409e-83  0.9617653 0.748 0.142  7.780474e-79
## HEMGN       5.809395e-142  0.9581669 0.804 0.103 1.623319e-137
## EGLN3       8.196729e-128  0.9561446 0.785 0.110 2.290412e-123
## ZC3HAV1L    1.166295e-134  0.9560348 0.748 0.093 3.258977e-130
## PTPN12       3.862978e-42  0.9527721 0.925 0.645  1.079432e-37
## ANXA3       1.141744e-127  0.9441462 0.748 0.097 3.190375e-123
## KCNA3        6.554687e-24  0.9334664 0.813 0.552  1.831576e-19
## PDZK1IP1    6.770486e-262  0.9330653 0.776 0.046 1.891877e-257
## CASP3        6.174896e-22  0.9329074 0.757 0.608  1.725451e-17
## MOB3C        2.384832e-30  0.9327554 0.673 0.348  6.663935e-26
## XK           0.000000e+00  0.9325759 0.729 0.025  0.000000e+00
## SUPT4H1      1.020500e-29  0.9254309 1.000 0.943  2.851582e-25
## HBD         2.522880e-105  0.9239379 0.439 0.036 7.049683e-101
## UIMC1        9.777910e-24  0.9180396 0.888 0.834  2.732241e-19
## SWI5         5.614072e-48  0.9165638 0.897 0.579  1.568740e-43
## HK1          6.180109e-32  0.9164114 0.916 0.819  1.726908e-27
## INF2         4.801821e-47  0.9156131 0.841 0.439  1.341773e-42
## MAGED2       2.019574e-43  0.9154733 0.944 0.745  5.643297e-39
## LRRC8B       9.130960e-36  0.9117750 0.692 0.312  2.551464e-31
## UXS1         2.013726e-45  0.9112758 0.925 0.677  5.626954e-41
## HMG20B       4.528561e-38  0.9059887 0.888 0.756  1.265416e-33
## PTK2         6.940892e-62  0.9031049 0.860 0.333  1.939493e-57
## FKBP8        9.215571e-25  0.9017661 0.981 0.968  2.575107e-20
## ARG2        3.443190e-228  0.8967344 0.832 0.065 9.621305e-224
## STX11        2.357198e-23  0.8929592 0.869 0.624  6.586719e-19
## PBX1        1.135319e-104  0.8923788 0.841 0.166 3.172422e-100
## BNIP3L       3.670707e-17  0.8923093 0.935 0.906  1.025706e-12
## ACTR3B       3.947048e-59  0.8876060 0.804 0.285  1.102924e-54
## TAX1BP3      1.308281e-46  0.8866987 0.897 0.600  3.655729e-42
## SPOCD1      5.359968e-220  0.8845747 0.776 0.057 1.497736e-215
## NCK2         5.485115e-52  0.8818660 0.888 0.483  1.532706e-47
## CERS2        2.118680e-39  0.8799288 0.916 0.743  5.920227e-35
## PTP4A2       8.981008e-21  0.8784660 0.991 0.967  2.509563e-16
## GLA          1.111263e-25  0.8784293 0.757 0.566  3.105202e-21
## SERINC3      1.067657e-29  0.8775357 0.963 0.900  2.983354e-25
## ARL6IP5      2.953021e-23  0.8774279 1.000 0.988  8.251627e-19
## PPP3R1       8.671239e-40  0.8766704 0.925 0.699  2.423004e-35
## EIF1B        3.213806e-20  0.8753408 0.953 0.963  8.980337e-16
## ATP2A3       3.195173e-33  0.8746690 0.897 0.798  8.928272e-29
## AL034397.3   3.531700e-28  0.8744867 0.785 0.398  9.868628e-24
## SSBP2        6.272867e-35  0.8727896 0.888 0.719  1.752827e-30
## CD47         4.954947e-15  0.8716650 0.991 0.994  1.384561e-10
## AQP10        0.000000e+00  0.8709824 0.766 0.016  0.000000e+00
## GABARAPL2    4.554746e-28  0.8659656 0.981 0.960  1.272733e-23
## MAP2K3       1.873825e-23  0.8656328 0.907 0.847  5.236029e-19
## CGRRF1       4.275604e-17  0.8639870 0.729 0.614  1.194732e-12
## SLC10A3      1.995258e-32  0.8604387 0.813 0.611  5.575351e-28
## CAPZB        2.624566e-24  0.8599902 1.000 0.993  7.333824e-20
## VPS37B       3.539113e-24  0.8561933 0.897 0.826  9.889343e-20
## TBXAS1       1.655633e-15  0.8560195 0.841 0.591  4.626336e-11
## MEPCE        1.004070e-39  0.8550877 0.841 0.542  2.805673e-35
## UBE2E3       7.269997e-41  0.8545556 0.981 0.824  2.031455e-36
## ABHD16A      2.374634e-32  0.8494760 0.832 0.652  6.635440e-28
## EIF4G2       1.506387e-24  0.8488485 0.981 0.990  4.209297e-20
## PKHD1L1     3.948654e-185  0.8480790 0.785 0.071 1.103372e-180
## SRSF8        2.851227e-35  0.8425923 0.935 0.805  7.967185e-31
## STX7         1.227128e-15  0.8400269 0.879 0.811  3.428964e-11
## RAC1         3.506481e-18  0.8397100 0.972 0.953  9.798160e-14
## RAB31        6.251094e-29  0.8386185 0.925 0.490  1.746743e-24
## PLEKHO1      1.598012e-34  0.8360851 0.935 0.676  4.465324e-30
## EIF4E        5.333651e-21  0.8330635 0.897 0.882  1.490382e-16
## RGCC         2.016642e-20  0.8284901 0.794 0.571  5.635103e-16
## ANKRD28      4.001616e-38  0.8279327 0.869 0.587  1.118172e-33
## TFPI         4.650751e-43  0.8179927 0.832 0.464  1.299559e-38
## TSPAN18     1.427395e-103  0.8175692 0.710 0.109  3.988571e-99
## NAA38        3.463766e-22  0.8160673 0.991 0.959  9.678802e-18
## ARMCX3       3.123247e-44  0.8154768 0.925 0.712  8.727290e-40
## HTATIP2      8.406166e-19  0.8153329 0.850 0.825  2.348935e-14
## SPHK1        2.574665e-56  0.8141772 0.804 0.288  7.194387e-52
## IL6ST        2.777539e-27  0.8139960 0.925 0.783  7.761278e-23
## DAP          3.323625e-31  0.8109883 0.860 0.749  9.287204e-27
## TUBA1B       2.206990e-22  0.8101951 1.000 0.952  6.166991e-18
## RHOF         1.796442e-18  0.8010583 0.888 0.787  5.019799e-14
## NT5DC3       4.641306e-21  0.8006156 0.561 0.291  1.296920e-16
## YWHAE        4.234606e-31  0.7999126 0.981 0.923  1.183276e-26
## LY6G6F       0.000000e+00  0.7985662 0.813 0.019  0.000000e+00
## PNP          5.964656e-31  0.7981192 0.897 0.784  1.666704e-26
## YIF1B        8.939262e-40  0.7966542 0.935 0.799  2.497898e-35
## GNAZ        6.869875e-189  0.7965159 0.804 0.074 1.919649e-184
## RHEB         5.674030e-37  0.7950470 0.935 0.808  1.585494e-32
## DCLRE1A      2.980292e-64  0.7918369 0.664 0.152  8.327830e-60
## HHEX         9.724722e-10  0.7895102 0.682 0.481  2.717379e-05
## RPA1         6.583654e-33  0.7778641 0.916 0.748  1.839671e-28
## SEMA4D       1.045824e-38  0.7777186 0.981 0.841  2.922347e-34
## UBA7         1.618011e-36  0.7751581 0.916 0.799  4.521209e-32
## STRN4        2.471315e-36  0.7735694 0.832 0.502  6.905595e-32
## RNF10        3.329578e-25  0.7678167 0.916 0.895  9.303841e-21
## TBC1D20      2.054175e-32  0.7676601 0.841 0.663  5.739982e-28
## ACP1         3.796947e-21  0.7673183 0.953 0.935  1.060981e-16
## PNKD         2.275172e-26  0.7656327 0.963 0.921  6.357512e-22
## CDIP1        2.710492e-37  0.7637841 0.869 0.619  7.573927e-33
## LINC02284    0.000000e+00  0.7617681 0.673 0.017  0.000000e+00
## MT-ND2       3.756746e-15  0.7616859 1.000 1.000  1.049748e-10
## TST          2.532150e-42  0.7589511 0.757 0.323  7.075587e-38
## IKBKG        1.734013e-37  0.7578654 0.925 0.797  4.845351e-33
## DIAPH1       4.430656e-18  0.7575282 0.944 0.914  1.238058e-13
## BAMBI       3.188943e-158  0.7570878 0.364 0.015 8.910863e-154
## HGD         1.679127e-307  0.7556406 0.720 0.032 4.691986e-303
## DENND4C      5.314864e-20  0.7555158 0.822 0.758  1.485133e-15
## LINC01011    5.696065e-78  0.7552571 0.822 0.221  1.591651e-73
## PDLIM7       8.393337e-38  0.7548869 0.850 0.487  2.345350e-33
## HIST1H2BN    5.520423e-23  0.7486783 0.664 0.402  1.542572e-18
## PDGFA        9.468382e-09  0.7459432 0.972 0.887  2.645750e-04
## PARK7        1.356814e-19  0.7425930 0.981 0.984  3.791345e-15
## PARD3        0.000000e+00  0.7425616 0.654 0.008  0.000000e+00
## JAM3         2.251687e-93  0.7422465 0.766 0.147  6.291889e-89
## ZCCHC17      5.883981e-35  0.7415737 0.897 0.763  1.644161e-30
## GCLM         1.439365e-33  0.7413876 0.804 0.514  4.022016e-29
## CTNNAL1      8.011008e-92  0.7405076 0.673 0.107  2.238516e-87
## TRAPPC3L     7.997918e-57  0.7371917 0.804 0.300  2.234858e-52
## GATA2        0.000000e+00  0.7371460 0.626 0.012  0.000000e+00
## TSPAN9       0.000000e+00  0.7370231 0.776 0.019  0.000000e+00
## HDGF         3.684407e-28  0.7370092 0.879 0.684  1.029534e-23
## DOK2         1.239255e-13  0.7370075 0.953 0.871  3.462850e-09
## HNRNPLL      1.995473e-20  0.7295451 0.776 0.584  5.575952e-16
## AP2M1        9.756974e-22  0.7276813 1.000 0.972  2.726391e-17
## C5orf30      3.023592e-50  0.7254974 0.645 0.184  8.448823e-46
## MTFR1L       3.556057e-29  0.7251519 0.813 0.647  9.936691e-25
## ABI1         2.402977e-18  0.7238919 0.935 0.923  6.714638e-14
## IFI27L2      2.968469e-14  0.7217705 0.935 0.927  8.294792e-10
## YBX3         2.881471e-11  0.7212505 0.766 0.606  8.051694e-07
## SERPINB1     1.050578e-15  0.7175947 0.963 0.972  2.935630e-11
## PACSIN2      1.671265e-23  0.7151436 0.785 0.656  4.670015e-19
## BTK          3.472288e-30  0.7149630 0.850 0.457  9.702615e-26
## PEAR1        0.000000e+00  0.7146202 0.738 0.008  0.000000e+00
## GNB5         4.481160e-35  0.7112557 0.841 0.571  1.252170e-30
## TOP1         1.195265e-08  0.7094304 0.879 0.911  3.339928e-04
## TGFB1I1      1.794412e-98  0.7086762 0.757 0.136  5.014125e-94
## PELI2        1.055980e-22  0.7073409 0.682 0.393  2.950726e-18
## CTDSPL      2.588227e-148  0.7070436 0.822 0.105 7.232283e-144
## SLC44A1      1.232356e-26  0.7058025 0.822 0.632  3.443571e-22
## RAP1A        2.556568e-08  0.7045030 0.953 0.964  7.143819e-04
## WIPI1        2.369535e-36  0.7019102 0.785 0.439  6.621190e-32
## P2RY1        1.932550e-85  0.7012568 0.720 0.137  5.400125e-81
## PBXIP1       2.583145e-30  0.7001607 0.963 0.854  7.218082e-26
## RGS3         4.046340e-12  0.6967239 0.710 0.610  1.130669e-07
## HEXIM1       6.348199e-22  0.6964872 0.785 0.666  1.773877e-17
## PHKB         1.179552e-27  0.6926173 0.888 0.784  3.296021e-23
## AIG1         7.487786e-44  0.6885595 0.850 0.510  2.092312e-39
## SERPINE1    3.956076e-128  0.6838366 0.617 0.062 1.105446e-123
## CCS          1.975921e-16  0.6837062 0.879 0.880  5.521316e-12
## ARHGDIB      3.681051e-17  0.6829753 1.000 1.000  1.028596e-12
## RHOBTB1     1.616375e-270  0.6791786 0.757 0.042 4.516637e-266
## DGKD         1.774457e-29  0.6780609 0.897 0.785  4.958366e-25
## MOB2         6.817985e-27  0.6753980 0.850 0.781  1.905150e-22
## CABP5        0.000000e+00  0.6749320 0.720 0.018  0.000000e+00
## PROS1       1.075753e-132  0.6723866 0.636 0.064 3.005975e-128
## AC100810.1   6.880715e-33  0.6687461 0.850 0.605  1.922678e-28
## PIP4K2A      3.035192e-29  0.6673676 0.907 0.782  8.481236e-25
## TMEM219      2.758475e-22  0.6633705 0.991 0.963  7.708006e-18
## PHF20L1      2.731335e-22  0.6630029 0.879 0.849  7.632170e-18
## WHAMM        1.615246e-31  0.6580241 0.916 0.842  4.513482e-27
## KIFAP3       9.086431e-23  0.6579471 0.766 0.609  2.539021e-18
## ARL8B        1.611630e-20  0.6576041 0.907 0.844  4.503377e-16
## CPNE5        9.986401e-69  0.6572004 0.813 0.205  2.790500e-64
## HIST1H2AE    2.271400e-43  0.6560102 0.738 0.303  6.346972e-39
## CRAT         2.929121e-41  0.6557072 0.813 0.446  8.184843e-37
## BET1         7.193876e-27  0.6550973 0.813 0.644  2.010185e-22
## SNX9         4.205177e-26  0.6545698 0.794 0.573  1.175053e-21
## MAP4K2       8.937000e-24  0.6513379 0.822 0.726  2.497266e-19
## MCTP1        7.993094e-34  0.6508573 0.860 0.435  2.233510e-29
## FLI1         2.699560e-13  0.6476140 0.925 0.952  7.543380e-09
## MAD2L1BP     1.204828e-13  0.6449215 0.636 0.501  3.366650e-09
## FNBP1L      6.929060e-114  0.6444866 0.626 0.072 1.936187e-109
## ABHD4        6.189023e-47  0.6418044 0.766 0.315  1.729399e-42
## CREG1        2.178266e-21  0.6412710 0.869 0.577  6.086730e-17
## VASP         3.484638e-11  0.6411233 0.972 0.954  9.737125e-07
## RGS6         0.000000e+00  0.6400721 0.776 0.025  0.000000e+00
## ZNF24        4.675560e-09  0.6384470 0.850 0.881  1.306492e-04
## TRIM13       8.605502e-10  0.6381048 0.673 0.623  2.404636e-05
## VTI1B        2.849210e-21  0.6304099 0.879 0.854  7.961546e-17
## ZNF438       1.898685e-53  0.6263315 0.860 0.393  5.305496e-49
## TSC22D3      3.427137e-14  0.6253669 1.000 0.996  9.576448e-10
## WRB          6.547754e-23  0.6240913 0.720 0.512  1.829639e-18
## SERPINE2     6.845056e-62  0.6239627 0.692 0.177  1.912714e-57
## MIGA2        1.862859e-32  0.6236828 0.766 0.467  5.205388e-28
## MITF         4.163206e-58  0.6223749 0.692 0.185  1.163325e-53
## SMPD1        2.662514e-15  0.6216260 0.776 0.680  7.439863e-11
## ARF3         4.139421e-27  0.6198516 0.925 0.833  1.156678e-22
## NDUFA5       6.619627e-26  0.6195196 0.935 0.904  1.849722e-21
## NCK1-DT      9.209999e-36  0.6190517 0.692 0.312  2.573550e-31
## UBE2F        1.171657e-20  0.6190012 0.804 0.688  3.273960e-16
## MTHFD2L      3.475791e-32  0.6174207 0.794 0.561  9.712402e-28
## ALDOA        2.019139e-13  0.6147875 1.000 0.991  5.642081e-09
## ZFAND6       2.291373e-16  0.6135907 0.888 0.878  6.402783e-12
## SRC          4.639475e-48  0.6119558 0.692 0.222  1.296409e-43
## MICU1        1.661385e-22  0.6108221 0.832 0.742  4.642407e-18
## ZFAND3       2.327014e-27  0.6089578 0.850 0.795  6.502375e-23
## ADD3         2.407433e-11  0.6068602 0.981 0.973  6.727091e-07
## FHL2         1.240493e-89  0.6059260 0.701 0.124  3.466309e-85
## PCNP         2.290544e-23  0.6030317 0.972 0.935  6.400466e-19
## MAFG         6.486599e-32  0.6015628 0.720 0.342  1.812550e-27
## ARHGAP21     2.291303e-43  0.6013469 0.804 0.382  6.402588e-39
## EPS15L1      1.350905e-20  0.6001476 0.822 0.736  3.774833e-16
## RASA3        3.613956e-22  0.5946435 0.944 0.857  1.009848e-17
## RMC1         4.584361e-09  0.5945015 0.692 0.689  1.281008e-04
## HPSE         1.053553e-10  0.5942875 0.598 0.434  2.943944e-06
## STXBP2       9.328693e-15  0.5941401 0.953 0.898  2.606717e-10
## STIM1        2.482304e-18  0.5935883 0.850 0.792  6.936303e-14
## PCMT1        2.818386e-16  0.5906931 0.944 0.906  7.875417e-12
## RTN4         8.241746e-10  0.5880746 0.981 0.956  2.302991e-05
## PECAM1       6.038293e-19  0.5870662 0.953 0.775  1.687280e-14
## PRKCD        1.038098e-19  0.5863701 0.879 0.673  2.900757e-15
## EHD1         1.047292e-20  0.5857653 0.925 0.854  2.926449e-16
## TSC22D4      1.473788e-07  0.5829435 0.888 0.946  4.118207e-03
## HSPB1        2.480690e-09  0.5824440 0.888 0.886  6.931792e-05
## ZNF778       8.660972e-25  0.5821404 0.654 0.361  2.420135e-20
## GNA15        5.953846e-32  0.5814142 0.776 0.362  1.663683e-27
## ARHGEF12     1.177078e-21  0.5782002 0.776 0.641  3.289110e-17
## TSPAN33      1.622846e-67  0.5775048 0.748 0.197  4.534719e-63
## BEX4         5.656950e-26  0.5764796 0.860 0.705  1.580722e-21
## RBM38        9.382923e-20  0.5748784 0.757 0.626  2.621870e-15
## PRKAR1A      2.267515e-18  0.5743777 0.925 0.924  6.336116e-14
## AP001033.1  5.369742e-290  0.5740134 0.701 0.032 1.500467e-285
## NUTM2A-AS1   1.043662e-15  0.5737398 0.860 0.837  2.916304e-11
## BRD3         1.298202e-18  0.5714905 0.748 0.678  3.627565e-14
## WDR11-AS1   2.814761e-112  0.5702100 0.645 0.079 7.865287e-108
## N4BP2L1      4.378587e-24  0.5665550 0.907 0.823  1.223509e-19
## ITFG1        2.816338e-22  0.5659464 0.860 0.758  7.869693e-18
## EPB41        1.672223e-13  0.5635762 0.888 0.886  4.672692e-09
## SSFA2        1.688819e-24  0.5632567 0.813 0.557  4.719066e-20
## RIT1         6.011178e-29  0.5615583 0.888 0.732  1.679703e-24
## TENT5C       1.903339e-18  0.5613597 0.776 0.501  5.318500e-14
## H1F0         1.999126e-41  0.5602859 0.776 0.314  5.586159e-37
## SPX         1.745513e-201  0.5585708 0.682 0.047 4.877487e-197
## GNAQ         1.627936e-24  0.5581892 0.869 0.638  4.548942e-20
## STMP1        5.102699e-15  0.5581106 0.897 0.961  1.425847e-10
## MSN          3.050553e-16  0.5560420 0.991 0.990  8.524161e-12
## NENF         5.690325e-16  0.5552799 0.757 0.617  1.590048e-11
## CHMP6        2.615093e-24  0.5550973 0.794 0.687  7.307353e-20
## DCTN2        3.371733e-23  0.5545086 0.935 0.880  9.421635e-19
## GTF3C6       5.869910e-13  0.5537093 0.860 0.896  1.640229e-08
## LANCL3       9.713110e-37  0.5516541 0.701 0.306  2.714134e-32
## TMEM164      3.381189e-29  0.5515335 0.720 0.382  9.448058e-25
## PADI4        4.676777e-30  0.5515043 0.794 0.405  1.306832e-25
## SERF2        7.012891e-08  0.5514500 1.000 1.000  1.959612e-03
## CD82         7.763164e-28  0.5498710 0.935 0.701  2.169261e-23
## XIRP2        0.000000e+00  0.5478272 0.262 0.002  0.000000e+00
## CRYL1        5.229145e-32  0.5476575 0.850 0.645  1.461180e-27
## ORAI2        1.397301e-22  0.5474244 0.841 0.735  3.904478e-18
## TRAPPC1      8.962150e-07  0.5428986 0.981 0.988  2.504294e-02
## MISP3       1.790578e-102  0.5428028 0.692 0.102  5.003411e-98
## MINK1        3.975705e-28  0.5415787 0.832 0.691  1.110931e-23
## RAB11B       6.776442e-24  0.5415297 0.991 0.955  1.893541e-19
## TERF2IP      1.159118e-14  0.5415054 0.963 0.953  3.238924e-10
## PCMTD1       2.972637e-23  0.5408221 0.907 0.838  8.306438e-19
## PHTF2        6.185098e-18  0.5402861 0.813 0.721  1.728302e-13
## KLF3         2.151813e-09  0.5385303 0.879 0.901  6.012810e-05
## HIST1H2BO    4.965153e-85  0.5347372 0.383 0.034  1.387413e-80
## F2RL3        4.578757e-87  0.5339539 0.720 0.135  1.279442e-82
## CDK5RAP2     2.335907e-29  0.5314064 0.813 0.599  6.527226e-25
## ANKRD9       7.215073e-79  0.5293369 0.626 0.108  2.016108e-74
## SCYL2        8.392936e-20  0.5285061 0.785 0.682  2.345238e-15
## USP39        4.574138e-14  0.5272452 0.757 0.737  1.278151e-09
## RHOA         5.393021e-14  0.5259249 1.000 0.999  1.506972e-09
## GDI1         1.255596e-15  0.5255439 0.860 0.861  3.508513e-11
## MXD1         1.527110e-09  0.5248313 0.729 0.694  4.267204e-05
## CALD1        2.299706e-95  0.5244420 0.710 0.119  6.426068e-91
## ITGB5       1.082720e-294  0.5229493 0.701 0.031 3.025444e-290
## EMD          1.245515e-14  0.5225092 0.879 0.889  3.480341e-10
## LINC00211   1.689830e-141  0.5223276 0.729 0.082 4.721892e-137
## VPS28        2.243921e-14  0.5193633 0.972 0.987  6.270190e-10
## SUSD3        7.270351e-19  0.5192844 0.748 0.531  2.031554e-14
## LINC01151   1.540633e-274  0.5187484 0.720 0.036 4.304990e-270
## RHOC         9.225871e-17  0.5177565 0.841 0.632  2.577985e-12
## RABGAP1L     3.940461e-11  0.5172724 0.907 0.930  1.101083e-06
## SF3A1        5.354565e-11  0.5169988 0.869 0.893  1.496226e-06
## AKIRIN1      3.240751e-19  0.5164984 0.879 0.839  9.055629e-15
## ORAI1        4.083298e-20  0.5163613 0.869 0.779  1.140996e-15
## MAP1LC3B     1.128474e-14  0.5143517 0.963 0.937  3.153296e-10
## AMIGO2       1.762993e-26  0.5141721 0.579 0.248  4.926331e-22
## CAPN2        7.717738e-14  0.5141463 0.972 0.932  2.156567e-09
## PLOD2       5.728660e-212  0.5133753 0.654 0.040 1.600759e-207
## EPOR         1.280603e-30  0.5131580 0.682 0.352  3.578390e-26
## HDAC5        4.447202e-24  0.5130541 0.860 0.683  1.242682e-19
## ADI1         7.089057e-16  0.5124758 0.841 0.785  1.980895e-11
## TECPR2       5.844768e-13  0.5119514 0.570 0.418  1.633204e-08
## RYBP         3.012259e-27  0.5114188 0.804 0.529  8.417154e-23
## MORF4L1      9.675523e-09  0.5106555 0.991 0.991  2.703631e-04
## TWSG1        5.142743e-33  0.5077897 0.645 0.271  1.437037e-28
## TMOD3        2.937292e-21  0.5043707 0.925 0.929  8.207675e-17
## GUCY1A1     1.480010e-123  0.5013164 0.692 0.083 4.135592e-119
## AHCTF1       2.398824e-20  0.5010947 0.813 0.708  6.703033e-16
## WASHC1       1.209771e-12  0.4992260 0.972 0.969  3.380462e-08
## SYMPK        1.950157e-24  0.4985817 0.869 0.742  5.449324e-20
## TAOK3        1.564051e-11  0.4950276 0.963 0.952  4.370427e-07
## TM6SF1       3.456106e-51  0.4949792 0.766 0.272  9.657397e-47
## NDUFB4       3.135830e-09  0.4938730 0.981 0.979  8.762451e-05
## SLFN14       0.000000e+00  0.4911333 0.589 0.015  0.000000e+00
## MAPK14       1.866660e-07  0.4907773 0.664 0.646  5.216009e-03
## SRSF6        1.943625e-12  0.4907610 0.850 0.835  5.431071e-08
## RNF115       1.554052e-10  0.4898937 0.785 0.811  4.342487e-06
## ATP9A       2.856098e-142  0.4898907 0.645 0.061 7.980793e-138
## AP001189.3   0.000000e+00  0.4893590 0.561 0.016  0.000000e+00
## ATP2C1       1.329872e-24  0.4893317 0.766 0.555  3.716061e-20
## TMEM185A     3.975468e-30  0.4887431 0.729 0.426  1.110865e-25
## ASB8         4.725083e-15  0.4882883 0.813 0.805  1.320330e-10
## TSC2         5.019292e-16  0.4880102 0.813 0.761  1.402541e-11
## DGKG         2.629631e-56  0.4859739 0.682 0.184  7.347978e-52
## KAT6A        2.167364e-15  0.4831822 0.850 0.879  6.056265e-11
## DLST         5.194039e-07  0.4829342 0.720 0.784  1.451370e-02
## CCPG1        1.330693e-18  0.4813330 0.879 0.805  3.718355e-14
## WFDC1        5.177879e-11  0.4786444 0.355 0.165  1.446855e-06
## NT5M        3.672967e-204  0.4765973 0.701 0.049 1.026337e-199
## VAPB         1.765929e-22  0.4765206 0.748 0.593  4.934534e-18
## ATL1         4.473839e-68  0.4753848 0.701 0.164  1.250125e-63
## CMAS         3.872987e-12  0.4728515 0.692 0.650  1.082229e-07
## GRHL1       6.165863e-109  0.4724076 0.589 0.067 1.722927e-104
## HIST1H2BG    1.270140e-56  0.4692003 0.645 0.160  3.549153e-52
## MSANTD3      4.530545e-42  0.4675706 0.673 0.241  1.265970e-37
## KLF9         2.942684e-10  0.4673185 0.738 0.674  8.222743e-06
## FN3K         1.149433e-35  0.4653946 0.551 0.174  3.211862e-31
## TTLL7        9.407360e-78  0.4651854 0.626 0.108  2.628699e-73
## PANX1        5.770598e-26  0.4637096 0.682 0.384  1.612478e-21
## MPL          0.000000e+00  0.4633860 0.570 0.016  0.000000e+00
## SYTL4       4.173376e-136  0.4633082 0.617 0.058 1.166166e-131
## SELENOT      1.535354e-10  0.4620668 0.953 0.952  4.290239e-06
## LINC01089    4.431013e-29  0.4619490 0.776 0.506  1.238158e-24
## UNC13D       2.681850e-16  0.4600827 0.841 0.798  7.493894e-12
## MTSS1        1.106052e-15  0.4600437 0.897 0.735  3.090642e-11
## YWHAQ        3.119072e-12  0.4596159 0.944 0.953  8.715623e-08
## CFAP161      0.000000e+00  0.4584249 0.523 0.013  0.000000e+00
## KLHL6        3.796417e-20  0.4576029 0.710 0.523  1.060833e-15
## PYGB         3.090293e-17  0.4573558 0.729 0.605  8.635207e-13
## RAB6B       1.915072e-146  0.4558996 0.607 0.051 5.351286e-142
## SEPT4        2.474993e-64  0.4530366 0.626 0.132  6.915873e-60
## SLBP         4.472201e-13  0.4527023 0.869 0.805  1.249667e-08
## LINC00534    0.000000e+00  0.4526788 0.607 0.019  0.000000e+00
## CALM1        2.486752e-11  0.4503843 1.000 0.998  6.948732e-07
## ATF4         1.748276e-13  0.4496265 0.935 0.913  4.885208e-09
## LPAR5        4.317594e-32  0.4493893 0.664 0.280  1.206465e-27
## INAFM2       5.975619e-54  0.4484714 0.720 0.222  1.669767e-49
## LRP12        1.709617e-60  0.4439938 0.561 0.109  4.777182e-56
## TTC33        4.196728e-27  0.4421813 0.701 0.398  1.172692e-22
## RBPMS2       4.336679e-87  0.4404606 0.486 0.054  1.211798e-82
## TOLLIP       4.657754e-19  0.4368302 0.850 0.732  1.301516e-14
## TMEM39B      1.384108e-06  0.4344875 0.570 0.547  3.867613e-02
## TANGO2       5.843599e-19  0.4344491 0.757 0.670  1.632877e-14
## YPEL2        6.170234e-10  0.4326104 0.710 0.662  1.724149e-05
## GOLGA2       1.924407e-09  0.4322203 0.710 0.721  5.377370e-05
## PKIG         3.507997e-47  0.4317437 0.766 0.241  9.802396e-43
## NAP1L4       2.478619e-14  0.4311727 0.907 0.906  6.926005e-10
## TSPOAP1-AS1  5.598423e-36  0.4306452 0.804 0.457  1.564367e-31
## AL157895.1  1.654775e-159  0.4298780 0.654 0.055 4.623937e-155
## LRRFIP2      3.306093e-09  0.4291645 0.804 0.801  9.238215e-05
## MBP          1.122038e-07  0.4265520 0.925 0.942  3.135312e-03
## STX1A        1.981376e-77  0.4264847 0.636 0.112  5.536559e-73
## TVP23B       1.137608e-23  0.4256256 0.822 0.638  3.178818e-19
## CDS2         5.974715e-10  0.4255160 0.841 0.858  1.669515e-05
## RIPOR3       5.832403e-49  0.4254294 0.523 0.114  1.629748e-44
## NRDC         2.406516e-10  0.4250480 0.869 0.911  6.724528e-06
## IGF2BP2      4.993480e-47  0.4249285 0.701 0.233  1.395328e-42
## FUT8         7.771301e-15  0.4237250 0.664 0.522  2.171535e-10
## E2F3         2.224683e-12  0.4220703 0.692 0.599  6.216431e-08
## SLC6A4       5.009157e-97  0.4211098 0.607 0.081  1.399709e-92
## MADD         6.983460e-21  0.4210056 0.804 0.693  1.951388e-16
## TMEM64       3.493763e-34  0.4204625 0.645 0.261  9.762623e-30
## TRAM1        6.848880e-11  0.4197414 0.972 0.951  1.913783e-06
## ERBIN        7.853006e-07  0.4188621 0.832 0.879  2.194365e-02
## PTPRJ        4.967877e-21  0.4186918 0.804 0.638  1.388174e-16
## PDE4D        1.499318e-24  0.4181802 0.832 0.576  4.189544e-20
## HIST1H2BD    1.613068e-38  0.4164209 0.495 0.126  4.507397e-34
## NME4         1.225293e-07  0.4157467 0.710 0.679  3.423835e-03
## VAMP7        9.365839e-21  0.4147915 0.813 0.718  2.617096e-16
## POLR2E       6.848862e-12  0.4144038 0.972 0.958  1.913777e-07
## CRYM        8.545886e-141  0.4132462 0.327 0.013 2.387977e-136
## STARD3NL     6.468860e-16  0.4121325 0.850 0.815  1.807594e-11
## SUCNR1      3.265381e-139  0.4094270 0.364 0.017 9.124453e-135
## UBE2H        2.435841e-23  0.4077934 0.785 0.616  6.806471e-19
## FSTL1       2.234481e-269  0.4073621 0.551 0.020 6.243810e-265
## VIL1        2.695557e-289  0.4072133 0.682 0.030 7.532195e-285
## PVALB       3.318249e-195  0.4050588 0.598 0.036 9.272184e-191
## RALY         7.552070e-10  0.4049533 0.972 0.960  2.110275e-05
## PLA2G4A      3.712855e-13  0.4043761 0.374 0.160  1.037483e-08
## SMTN         6.689039e-24  0.4041456 0.383 0.109  1.869118e-19
## AP002478.1   0.000000e+00  0.4037521 0.636 0.010  0.000000e+00
## MYEOV       1.004821e-196  0.4034890 0.626 0.039 2.807770e-192
## AC008124.1   3.291016e-15  0.4005593 0.682 0.576  9.196087e-11
## PIK3CB       9.071085e-20  0.3999438 0.710 0.532  2.534733e-15
## TNFAIP8L1    2.102402e-11  0.3991390 0.598 0.484  5.874741e-07
## ZFAND2B      1.701454e-09  0.3987641 0.794 0.825  4.754372e-05
## CXCL3       3.292832e-179  0.3973460 0.579 0.036 9.201160e-175
## ACTR10       4.108610e-13  0.3962960 0.850 0.845  1.148069e-08
## CDKL1        8.217929e-25  0.3945210 0.598 0.283  2.296336e-20
## MTRNR2L6     1.899880e-09  0.3945131 0.981 0.966  5.308835e-05
## LYPLAL1-DT  5.761266e-226  0.3939883 0.626 0.033 1.609870e-221
## SCFD2        4.547981e-17  0.3937465 0.654 0.450  1.270842e-12
## ASAP1        4.609338e-15  0.3933598 0.794 0.641  1.287987e-10
## GRK5         1.287829e-25  0.3926103 0.720 0.450  3.598581e-21
## CASP6        3.119056e-19  0.3923767 0.682 0.460  8.715579e-15
## ANK1         1.964501e-88  0.3912175 0.626 0.094  5.489405e-84
## SLC50A1      2.378181e-20  0.3909813 0.869 0.769  6.645352e-16
## SAV1         2.040770e-25  0.3908135 0.654 0.338  5.702523e-21
## DYTN         0.000000e+00  0.3906174 0.467 0.007  0.000000e+00
## BCAP31       9.395317e-14  0.3887732 0.991 0.974  2.625333e-09
## USP12        2.004401e-25  0.3883781 0.794 0.535  5.600897e-21
## TSPAN13      1.306447e-65  0.3855966 0.701 0.134  3.650604e-61
## RAB30        1.369855e-21  0.3855765 0.664 0.352  3.827787e-17
## MPST         2.111006e-17  0.3853382 0.794 0.626  5.898783e-13
## ANXA7        3.208840e-10  0.3842212 0.935 0.922  8.966461e-06
## ADIPOR2      1.296429e-16  0.3838297 0.757 0.657  3.622611e-12
## RSPH9       1.049587e-206  0.3832815 0.589 0.032 2.932862e-202
## SLC9A9       7.079988e-12  0.3824713 0.720 0.627  1.978361e-07
## PRTFDC1     3.461110e-205  0.3803683 0.664 0.043 9.671379e-201
## CTNS         6.209887e-22  0.3801369 0.607 0.325  1.735229e-17
## SUSD1        7.282633e-15  0.3798153 0.626 0.441  2.034986e-10
## C21orf58     3.154249e-36  0.3793532 0.523 0.148  8.813917e-32
## MBTD1        6.423533e-15  0.3783826 0.636 0.468  1.794928e-10
## PXK          4.276029e-15  0.3768468 0.804 0.688  1.194851e-10
## SLC39A3      4.887799e-15  0.3764709 0.607 0.408  1.365798e-10
## DYNLRB1      1.401652e-11  0.3742977 0.981 0.971  3.916636e-07
## RAB13        2.192180e-33  0.3738602 0.748 0.330  6.125608e-29
## DCK          4.139963e-07  0.3733598 0.813 0.812  1.156830e-02
## PTPRA        2.157675e-13  0.3730758 0.813 0.820  6.029192e-09
## METTL22      4.699168e-19  0.3725392 0.748 0.585  1.313088e-14
## SLC9A3R1     1.079106e-09  0.3720858 0.935 0.902  3.015347e-05
## HIST1H2AM    1.523034e-18  0.3689219 0.579 0.309  4.255814e-14
## MAST4        2.782041e-10  0.3678418 0.645 0.550  7.773856e-06
## NEXN-AS1     6.027938e-64  0.3669306 0.477 0.072  1.684387e-59
## SH3TC2      1.246090e-126  0.3668451 0.561 0.050 3.481950e-122
## KLHL5        5.264093e-13  0.3660806 0.626 0.476  1.470945e-08
## PDK1         1.616533e-12  0.3651667 0.692 0.543  4.517079e-08
## STK40        6.664136e-15  0.3649063 0.729 0.598  1.862160e-10
## CALCOCO1     7.382924e-17  0.3634409 0.850 0.798  2.063011e-12
## BX255925.3   1.216530e-52  0.3633898 0.682 0.200  3.399350e-48
## CXCL5       3.313164e-137  0.3626362 0.514 0.038 9.257974e-133
## AATK         7.310068e-46  0.3625503 0.486 0.103  2.042652e-41
## AC074327.1   0.000000e+00  0.3624212 0.654 0.017  0.000000e+00
## AC078883.1   1.248986e-23  0.3611127 0.645 0.332  3.490042e-19
## ASAP2       1.378496e-241  0.3599254 0.533 0.021 3.851932e-237
## GK           1.328316e-21  0.3591681 0.776 0.482  3.711714e-17
## F11R         9.840571e-29  0.3588673 0.720 0.399  2.749751e-24
## VEPH1        0.000000e+00  0.3585106 0.645 0.016  0.000000e+00
## GNA13        8.664363e-13  0.3582465 0.794 0.771  2.421083e-08
## KLHDC8B      1.564195e-37  0.3579727 0.561 0.167  4.370831e-33
## ABTB1        1.489849e-12  0.3575461 0.888 0.894  4.163085e-08
## EGF          0.000000e+00  0.3574526 0.551 0.009  0.000000e+00
## CRKL         3.444854e-11  0.3571606 0.692 0.656  9.625955e-07
## BMP6         0.000000e+00  0.3567522 0.579 0.013  0.000000e+00
## TBC1D15      2.738787e-13  0.3565065 0.692 0.642  7.652994e-09
## EFNB1        1.847356e-34  0.3563204 0.551 0.177  5.162066e-30
## DENND2C      3.204037e-29  0.3560985 0.514 0.178  8.953040e-25
## TCEAL9       1.059924e-92  0.3556975 0.579 0.076  2.961745e-88
## RNF8         4.472907e-07  0.3553314 0.570 0.562  1.249864e-02
## FAM214B      9.206248e-10  0.3550487 0.617 0.484  2.572502e-05
## NEK7         7.822874e-14  0.3525986 0.785 0.719  2.185946e-09
## CAV2         7.733098e-56  0.3506573 0.551 0.114  2.160859e-51
## AFAP1        6.922573e-50  0.3504309 0.598 0.153  1.934375e-45
## CHD9         3.631881e-07  0.3499130 0.822 0.848  1.014857e-02
## KALRN        3.033095e-31  0.3495479 0.449 0.121  8.475377e-27
## SLC35D2      7.563341e-29  0.3467564 0.561 0.213  2.113424e-24
## TMSB4Y       8.945733e-39  0.3465331 0.486 0.122  2.499706e-34
## PDGFRA      1.396984e-150  0.3463762 0.486 0.030 3.903592e-146
## FURIN        8.197950e-16  0.3439925 0.710 0.500  2.290753e-11
## MAVS         4.104338e-12  0.3433564 0.776 0.726  1.146875e-07
## CD36         4.850925e-13  0.3418406 0.813 0.433  1.355494e-08
## RCOR3        1.204345e-07  0.3418039 0.692 0.730  3.365301e-03
## HIPK2        3.683171e-08  0.3413056 0.682 0.639  1.029188e-03
## SEPT7        4.727458e-11  0.3410440 0.981 0.988  1.320994e-06
## ARL15        1.308728e-16  0.3406603 0.607 0.411  3.656980e-12
## HBQ1        2.062942e-177  0.3361169 0.682 0.053 5.764478e-173
## LXN          2.097181e-09  0.3355275 0.430 0.267  5.860153e-05
## SLX4         2.724994e-31  0.3352396 0.626 0.260  7.614450e-27
## LUC7L2       8.330547e-09  0.3351763 0.841 0.901  2.327805e-04
## ACER3        9.599910e-13  0.3331336 0.710 0.563  2.682503e-08
## AL135925.1   2.289739e-10  0.3328562 0.654 0.593  6.398219e-06
## CPEB4        7.833312e-10  0.3321559 0.692 0.570  2.188862e-05
## HYI          2.307480e-37  0.3312859 0.636 0.225  6.447790e-33
## P2RY12      1.849090e-147  0.3308463 0.607 0.051 5.166911e-143
## AGBL5        5.357159e-28  0.3297275 0.589 0.250  1.496951e-23
## ABO          1.349029e-37  0.3296180 0.664 0.244  3.769590e-33
## CYTH2        3.428783e-13  0.3295029 0.682 0.601  9.581049e-09
## MCM6         1.625629e-13  0.3289419 0.570 0.365  4.542496e-09
## GNG8         2.783193e-52  0.3282268 0.439 0.073  7.777076e-48
## E2F1         2.861928e-67  0.3278192 0.402 0.046  7.997084e-63
## LAPTM4B      3.768126e-58  0.3265554 0.505 0.089  1.052927e-53
## PGD          3.560631e-10  0.3257505 0.916 0.829  9.949472e-06
## ST3GAL3      1.504297e-17  0.3257098 0.664 0.459  4.203458e-13
## LINC01003    5.745656e-15  0.3250503 0.607 0.400  1.605509e-10
## SEC14L5      4.822101e-81  0.3250231 0.495 0.062  1.347440e-76
## CXCR2        1.877138e-20  0.3247919 0.626 0.327  5.245286e-16
## EFHC2        1.992389e-87  0.3244868 0.570 0.077  5.567333e-83
## RHD          8.945542e-28  0.3244686 0.607 0.273  2.499653e-23
## ZFYVE21      6.317101e-15  0.3234349 0.607 0.425  1.765188e-10
## GRTP1       2.651681e-108  0.3224434 0.439 0.035 7.409592e-104
## ARMCX6       4.047207e-17  0.3206470 0.785 0.703  1.130911e-12
## ITGA9       7.156724e-224  0.3195388 0.636 0.035 1.999803e-219
## SLC18A2     1.855517e-147  0.3191409 0.542 0.039 5.184871e-143
## CCDC92       3.487244e-24  0.3171414 0.682 0.411  9.744406e-20
## LINC00853    0.000000e+00  0.3167887 0.636 0.018  0.000000e+00
## PYCR2        5.292253e-11  0.3165207 0.692 0.601  1.478814e-06
## DPCD         4.584349e-33  0.3149902 0.542 0.178  1.281005e-28
## SLMAP        2.473770e-13  0.3144319 0.804 0.767  6.912454e-09
## PRELID2      1.734744e-13  0.3129877 0.346 0.137  4.847394e-09
## SAMD14      9.511778e-202  0.3110496 0.449 0.018 2.657876e-197
## VKORC1L1     5.793138e-26  0.3107130 0.645 0.324  1.618777e-21
## TRBV7-4      1.767584e-84  0.3105214 0.523 0.066  4.939161e-80
## STK24        1.349929e-13  0.3104391 0.673 0.560  3.772107e-09
## UBE2J1       1.797904e-11  0.3086957 0.944 0.895  5.023882e-07
## HPGD         1.152022e-14  0.3077926 0.542 0.301  3.219094e-10
## WRNIP1       1.565508e-19  0.3062752 0.682 0.472  4.374499e-15
## AL359644.1   1.868977e-42  0.3039829 0.570 0.158  5.222482e-38
## ATP5S        7.859193e-08  0.3036698 0.738 0.780  2.196094e-03
## CTDSP1       5.008180e-10  0.3024605 0.925 0.881  1.399436e-05
## CHST8        0.000000e+00  0.3020627 0.327 0.002  0.000000e+00
## PCYT1B       9.139206e-55  0.3018480 0.542 0.111  2.553768e-50
## STRADB       4.123553e-09  0.3017211 0.598 0.503  1.152244e-04
## RALB         4.563092e-07  0.3015649 0.729 0.691  1.275065e-02
## HBP1         3.898317e-09  0.3009365 0.785 0.791  1.089307e-04
## KRT8         2.374205e-21  0.2998999 0.505 0.217  6.634242e-17
## LSM1         2.336803e-10  0.2986416 0.832 0.828  6.529727e-06
## HEXIM2       9.844493e-14  0.2958326 0.617 0.469  2.750847e-09
## RTN2         3.361733e-80  0.2951173 0.589 0.091  9.393691e-76
## LY6G5C       1.961521e-23  0.2951071 0.598 0.290  5.481077e-19
## BICD2        6.611587e-09  0.2941515 0.692 0.647  1.847476e-04
## IRX3        4.575663e-288  0.2939118 0.505 0.015 1.278577e-283
## TRAPPC2      5.494396e-12  0.2937109 0.832 0.802  1.535299e-07
## MSRB3        3.747676e-51  0.2934470 0.533 0.113  1.047213e-46
## PRR7         1.575057e-12  0.2931008 0.673 0.517  4.401181e-08
## SNAP29       2.731175e-09  0.2901090 0.757 0.744  7.631722e-05
## OXTR         1.331387e-51  0.2893931 0.523 0.109  3.720296e-47
## DUSP22       9.743353e-09  0.2873889 0.776 0.776  2.722585e-04
## SEPT6        1.228069e-06  0.2873015 0.953 0.957  3.431594e-02
## KCTD10       2.833852e-13  0.2861425 0.636 0.494  7.918632e-09
## CDC14B       1.615566e-25  0.2858438 0.607 0.280  4.514375e-21
## OSBP2        4.235871e-98  0.2851691 0.533 0.059  1.183629e-93
## TRBV7-5      0.000000e+00  0.2845580 0.495 0.006  0.000000e+00
## SMIM27       1.623418e-11  0.2842717 0.841 0.818  4.536318e-07
## DBN1         4.055685e-15  0.2842374 0.598 0.397  1.133280e-10
## TMCC2       2.340586e-218  0.2836780 0.505 0.021 6.540300e-214
## MEA1         1.217272e-07  0.2818125 0.907 0.907  3.401422e-03
## CDK2AP1      1.289106e-22  0.2817899 0.654 0.325  3.602150e-18
## UBASH3B      3.601941e-15  0.2817723 0.645 0.455  1.006490e-10
## AL355073.1  4.370204e-236  0.2817045 0.589 0.027 1.221166e-231
## ZNF367       3.016804e-44  0.2811426 0.467 0.096  8.429855e-40
## CYREN        9.496132e-16  0.2806175 0.692 0.552  2.653504e-11
## IRAK2        3.552773e-14  0.2799555 0.495 0.271  9.927515e-10
## NDST1        5.652388e-25  0.2795770 0.570 0.236  1.579447e-20
## FAM81B      2.916091e-255  0.2788937 0.449 0.013 8.148433e-251
## MGAT4B       2.585343e-19  0.2783417 0.645 0.405  7.224225e-15
## PDE3A       2.019422e-220  0.2767824 0.514 0.022 5.642871e-216
## SGMS1        9.366437e-07  0.2763341 0.598 0.587  2.617264e-02
## MCPH1-AS1    1.942971e-93  0.2761988 0.514 0.057  5.429244e-89
## SPSB1        6.354956e-48  0.2749448 0.458 0.086  1.775765e-43
## ARMC8        2.508998e-09  0.2742655 0.766 0.790  7.010893e-05
## ROCK2        1.904013e-08  0.2742226 0.598 0.528  5.320384e-04
## SKAP2        4.125377e-10  0.2733454 0.888 0.766  1.152754e-05
## FAM177A1     5.553179e-10  0.2729623 0.850 0.848  1.551725e-05
## PCGF5        2.986004e-10  0.2717734 0.907 0.885  8.343790e-06
## PITPNM2      1.293393e-35  0.2706456 0.654 0.257  3.614129e-31
## MDM1         1.841459e-16  0.2698311 0.654 0.459  5.145588e-12
## HIST1H2BF    8.259501e-18  0.2687194 0.477 0.215  2.307952e-13
## CLMN         3.717250e-10  0.2672700 0.570 0.397  1.038711e-05
## CGGBP1       5.226565e-07  0.2669938 0.888 0.909  1.460459e-02
## ADORA2B      3.868995e-51  0.2667574 0.458 0.081  1.081113e-46
## MCF2L        2.808018e-26  0.2652387 0.449 0.141  7.846443e-22
## WASF1        2.829577e-27  0.2652220 0.393 0.101  7.906688e-23
## ZNF792       6.954120e-10  0.2645144 0.374 0.198  1.943190e-05
## TNIK         8.504449e-08  0.2642993 0.720 0.565  2.376398e-03
## LRRC8D       2.476599e-14  0.2622868 0.720 0.586  6.920361e-10
## GTDC1        1.976765e-10  0.2617149 0.636 0.531  5.523674e-06
## HRASLS       0.000000e+00  0.2605060 0.449 0.009  0.000000e+00
## AC147067.1   5.783998e-19  0.2600464 0.645 0.397  1.616223e-14
## LRBA         1.270481e-06  0.2587119 0.757 0.755  3.550104e-02
## UBXN2A       2.163787e-08  0.2564860 0.645 0.670  6.046270e-04
## AFAP1L2      3.806139e-65  0.2559404 0.505 0.079  1.063549e-60
## THEM5       1.084704e-187  0.2525794 0.430 0.018 3.030987e-183
## TMEM106C     9.710117e-12  0.2509314 0.701 0.566  2.713298e-07
## PLXDC2       2.848983e-09  0.2505794 0.766 0.440  7.960913e-05

We retrieved the genes coding for inflammatory cytokines highlighted in the original study.

cytokines_Mega_ori_study <- c("PDGFA","TGFB1","TNFSF4","PF4V1","PF4","PPBP")
cytokines_Mega_ori_study %in% rownames(markersMega)

## [1] TRUE TRUE TRUE TRUE TRUE TRUE

Idents(integrated) <- "majorType"
VlnPlot(integrated, features = cytokines_Mega_ori_study,pt.size = 0.1)

We can compare with the expression of these cytokines in the S-S086-2 sample at the single cell and the metacell level.

Idents(SC.list[["S-S086-2"]]) <- "majorType"

pbmc <- pbmc[,pbmc$majorType %in% levels(SC.list[["S-S086-2"]])] 
pbmc$majorType <- factor(pbmc$majorType,levels =levels(SC.list[["S-S086-2"]]))
Idents(pbmc) <- "majorType"

VlnPlot(pbmc, features = cytokines_Mega_ori_study,pt.size = 0.1)

VlnPlot(SC.list[["S-S086-2"]], features = cytokines_Mega_ori_study,pt.size = 0.1)

# sampleList <- str_split_fixed(files,pattern = "/",n=4)[,4]
# sampleList <- str_split_fixed(sampleList,pattern = "_",n=2)[,1]
# 
# sampleLowMem <- unique(integrated$sampleID[integrated$Sex == "M" ])
# sum(integrated$size[integrated$sampleID %in% sampleLowMem])
# 
# sampleLowMemFileList <- files[sampleList %in% sampleLowMem]
# 
# saveRDS(sampleLowMemFileList,"../data/lowMemFileList.rds")
# 
# sizeAll <- aggregate(integrated@meta.data[,"size"],
#                       by = list(sampleID = integrated@meta.data[,"sampleID"]),FUN = sum)
# 
# sizeAll[order(sizeAll$x),]
# 
# sizeF <- aggregate(integrated@meta.data[integrated$Sex == "F","size"],
#                       by = list(sampleID = integrated@meta.data[integrated$Sex == "F","sampleID"]),FUN = sum)
# 
# largestF <- sizeF$sampleID[which.max(sizeF$x)]
# 
# sizeH <- aggregate(integrated@meta.data[integrated$Sex == "M","size"],
#                       by = list(sampleID = integrated@meta.data[integrated$Sex == "M","sampleID"]),FUN = sum)
# 
# largestH <- sizeH$sampleID[which.max(sizeH$x)]